Braitenberg robot (referred to the Braitenberg Vehicle) is a implementation of the vehicle that is designed by the Valentino Braitenberg. It is an experiment of a robot that has only two light sensors and two motors to operate, chasing or running from the light depending on the type of the Braitenberg vehicle (2a - 2b type).
The behaviour of the robots towards the light depends on the actuator connection type of the sensors, this behaviour is decided with the algorithm we coded with SMD Python Library.
Our algorithm can works as the various Braitenberg vehicle types such as love and agression. It is attracted by the light and goes towards it. The Braitenberg robot uses two Ambient Light Sensor Modules and two 100 RPM BDC Motors with Encoder. The Python code runs on the Raspberry Pi that is mounted on the robot.
How It Works
The behavior of the robot towards light is determined by the connection type between the sensors and actuators. This interaction is controlled by an algorithm developed using the SMD Python Library. The algorithm enables the robot to simulate various Braitenberg vehicle types, such as:
• Love (Attraction): The robot is drawn to the light source and moves towards it.
• Aggression: The robot moves rapidly towards bright stimuli, mimicking aggressive behavior.
These behaviors are driven by the real-time input from the sensors and executed through motor control.
Technical Specifications
• Sensors: Two Ambient Light Sensor Modules to detect light intensity.
• Actuators: Two 100 RPM Brushed DC Motors with Encoders for accurate and responsive motion.
• Controller: A Raspberry Pi mounted on the robot, running Python code to process inputs and control actions.
The Braitenberg Robot’s hardware setup and algorithm work seamlessly to mimic lifelike behaviors, making it a powerful tool for exploring robotics and behavior modeling.
Applications of Braitenberg Robot
1. Educational Use:
• Teaches fundamental concepts of sensor integration, motor control, and emergent behaviors.
• Demonstrates how bio-inspired designs can lead to practical robotics applications.
2. Research and Prototyping:
• Aids in understanding and testing autonomous behavior models.
• Serves as a platform for experimenting with simple AI-driven systems.
3. Hobbyist Projects:
• A creative and accessible robotics project for makers.
• Provides a foundation for further exploration in robotics.
Here is the code of the project:
from smd.red import *
import time
import sys
class Braitenberg:
""" Port and SMD ids are assigned. Modules connected to SMDs are printed.
The operation mode is set for velocity modes. Torque is enabled
"""
def __init__(self):
# SMD setup
self.port = "/dev/ttyUSB0"
self.m = Master(self.port)
self.m.attach(Red(0))
self.m.attach(Red(1))
print(self.m.scan_modules(0)) # Print the scanned modules for the first SMD ID.
print(self.m.scan_modules(1)) # Print the scanned modules for the second SMD ID.
# Motor setup
# SMD 0 is left motor
# SMD 1 is right motor
self.m.set_operation_mode(0, 2)
self.m.set_operation_mode(1, 2)
self.m.enable_torque(0, True)
self.m.enable_torque(1, True)
def map(self, value, fromLow, fromHigh, toLow, toHigh):
"""_summary_
Args:
value (_type_): value of light data from the light sensor
fromLow (_type_): minimum value of light coming from the light sensor
fromHigh (_type_): maximum value of light coming from the light sensor
toLow (_type_): minimum value of velocity
toHigh (_type_): maximum value of velocity
Returns:
_type_: Velocity value is returned in direct proportion to the incoming light value.
"""
return int((value - fromLow) * (toHigh - toLow) / (fromHigh - fromLow) + toLow)
def stop(self):
"""The motors are stopped by setting the Velocity value to 0.
"""
self.m.set_velocity(0, 0)
self.m.set_velocity(1, 0)
def get_light_values(self):
""" Incoming light data is assigned to right and left light variables
Returns:
_type_: right and left light values are returned
"""
left_light = self.m.get_light(0, 1)
right_light = self.m.get_light(0, 2)
return left_light, right_light
def fear(self):
""" The right motor is related to the light sensor on the right, the left motor is related to the light data
from the left sensor in direct proportion. Motor speeds increase in direct proportion to the light data, and
accordingly the robot tends to move away from the light.
"""
left_light, right_light = self.get_light_values()
if left_light is not None and right_light is not None:
# Adjust PWM values based on light intensity.
left_stim = self.map(left_light, 0, 2300, 40, 100)
right_stim = self.map(right_light, 0, 2300, 40, 100)
print(f"left_light {left_light}, righ_light {right_light} ")
self.m.set_velocity(0, -left_stim)
self.m.set_velocity(1, right_stim)
else:
self.stop() # Stop if any sensor is None.
def love(self):
"""
The right motor is related to the light sensor on the right, the left motor is inversely
related to the light data from the left sensor. Motor speeds increase inversely proportional to
the light data, and accordingly the robot tends to approach the light. However, as the robot
approaches the light source, its speed decreases.
"""
left_light, right_light = self.get_light_values()
if left_light is not None and right_light is not None:
# Adjust PWM values based on light intensity.
left_stim = self.map(left_light, 0, 1500, 100 ,0)
right_stim = self.map(right_light, 0, 1500, 100, 0)
if right_stim and left_stim > -1:
self.m.set_velocity(0, -left_stim)
self.m.set_velocity(1, right_stim)
else:
self.stop()
print(f"left_stim {left_stim}, right_stim {right_stim} ")
else:
self.stop() # Stop if any sensor is None.
def wander_around(self):
"""The right motor is inversely related to the light sensor on the left,
the left motor is inversely related to the light data from the right sensor.
Motor speeds increase inversely proportional to the light data, and accordingly
the robot tends to move away from the light. However, as the robot moves away from
the light source, its speed increases.
"""
left_light, right_light = self.get_light_values()
if left_light is not None and right_light is not None:
# Adjust PWM values based on light intensity.
left_stim = self.map(right_light, 0, 1500, 100, 0)
right_stim = self.map(left_light, 0, 1500, 100, 0)
self.m.set_velocity(0, right_stim)
self.m.set_velocity(1, -left_stim)
print(f"left pwm: {left_stim}, right pwm: {right_stim}")
else:
self.stop() # Stop if any sensor is None.
def agression(self):
""" The right motor is related to the light sensor on the right, the left motor is related to the light data
from the left sensor in direct proportion. Motor speeds increase in direct proportion to the light data, and
accordingly the robot tends to move away from the light.
"""
left_light, right_light = self.get_light_values()
if left_light is not None and right_light is not None:
left_stim = self.map(left_light, 0, 1500, 0, 100)
right_stim = self.map(right_light, 0, 1500, 0, 100)
self.m.set_velocity(0, -right_stim)
self.m.set_velocity(1, left_stim)
print(f"Left: {left_stim}, Right: {right_stim}")
else:
self.stop()
def run(self):
c = 0
while True:
button =self.m.get_button(0, 1)
if button == 1:
c += 1
time.sleep(0.4)
if c == 0:
print(0)
self.fear()
self.m.set_rgb(0, 1, red = 0, green = 0, blue = 255)
elif c == 1:
print(1)
self.love()
self.m.set_rgb(0, 1, red = 255, green = 0, blue = 255)
elif c == 2:
print(2)
self.agression()
self.m.set_rgb(0, 1, red = 255, green =0 , blue = 0)
elif c == 3:
print(3)
self.wander_around()
self.m.set_rgb(0, 1, red = 0, green = 255, blue = 0)
elif c > 2:
c = 0
if __name__ == "__main__":
try:
vehicle = Braitenberg()
vehicle.run()
except KeyboardInterrupt:
vehicle.stop()
sys.exit(0)
